Hyperspectral Anomaly Detection by Spatial–Spectral Fusion Based on Extreme Value-Entropy Band Selection and Cauchy Graph Distance Optimization

Hyperspectral Anomaly Detection by Spatial–Spectral Fusion Based on Extreme Value-Entropy Band Selection and Cauchy Graph Distance Optimization

Hyperspectral technology for detecting camouflaged targets in complex backgrounds represents a current research hotspot. Hyperspectral data often contain numerous spectral bands, which can lead to data redundancy. Traditional anomaly detection methods typically assume that the background spectrum fo...

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Bibliographic Details
Main Authors: Song Zhao, Yali Lv, Wen Zhang, Lijun Wang, Zhiru Yang, Gaofeng Ren, Bin Wang, Xiaobin Zhao, Tongwei Lu, Jiayao Wang, Wei Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Camouflage net detection
cauchy graph distance
extreme-entropy band selection
hyperspectral imaging
low-rank sparse representation
Online Access:https://ieeexplore.ieee.org/document/11045410/
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